Advancements in deep learning techniques and the availability of free, large databases
have made it possible, even for non-technical people, to either manipulate or generate …

In this paper, we consider the face swapping detection from the perspective of face identity.
Face swapping aims to replace the target face with the source face and generate the fake …

Deepfakes present an emerging threat in cyberspace. Recent developments in machine
learning make deepfakes highly believable, and very difficult to differentiate between what is …

In this paper, we analyse the generalization ability of binary classifiers for the task of
deepfake detection. We find that the stumbling block to their generalization is caused by the …

Misinformation has become a pressing issue. Fake media, in both visual and textual forms,
is widespread on the web. While various deepfake detection and text fake news detection …

State-of-the-art deepfake detectors perform well in identifying forgeries when they are
evaluated on a test set similar to the training set, but struggle to maintain good performance …

We present a novel high-resolution face swapping method using the inherent prior
knowledge of a pre-trained GAN model. Although previous research can leverage …

In this work, we propose a high fidelity face swapping method, called HifiFace, which can
well preserve the face shape of the source face and generate photo-realistic results. Unlike …

The great advancements of generative adversarial networks and face recognition models in
computer vision have made it possible to swap identities on images from single sources …

Numerous attempts have been made to the task of person-agnostic face swapping given its
wide applications. While existing methods mostly rely on tedious network and loss designs …